Triple
T3111557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiruchirappalli |
E64961
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
TN-81
TN-81 is a regional vehicle registration code assigned to a specific transport authority jurisdiction in the Tiruchirappalli area of Tamil Nadu, India.
|
E326582
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: TN-81 | Statement: [Tiruchirappalli, vehicleRegistrationCode, TN-81]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TN-81 Context triple: [Tiruchirappalli, vehicleRegistrationCode, TN-81]
-
A.
TX-10
TX-10 is the commonly used abbreviation for Texas's 10th congressional district, a U.S. House of Representatives district covering parts of central Texas.
-
B.
TX-12
TX-12 is a United States congressional district in north-central Texas that includes much of Fort Worth and surrounding areas and elects a member to the U.S. House of Representatives.
-
C.
TX-14
TX-14 is a U.S. congressional district in Texas that elects a representative to the United States House of Representatives.
-
D.
TX-38
TX-38 is a U.S. congressional district in Texas represented in the House of Representatives.
-
E.
T-68
The T-68 was an early generation light rail tram used on the Manchester Metrolink system in the UK before being superseded by newer models.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: TN-81 Triple: [Tiruchirappalli, vehicleRegistrationCode, TN-81]
Generated description
TN-81 is a regional vehicle registration code assigned to a specific transport authority jurisdiction in the Tiruchirappalli area of Tamil Nadu, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TN-81 Target entity description: TN-81 is a regional vehicle registration code assigned to a specific transport authority jurisdiction in the Tiruchirappalli area of Tamil Nadu, India.
-
A.
TX-10
TX-10 is the commonly used abbreviation for Texas's 10th congressional district, a U.S. House of Representatives district covering parts of central Texas.
-
B.
TX-12
TX-12 is a United States congressional district in north-central Texas that includes much of Fort Worth and surrounding areas and elects a member to the U.S. House of Representatives.
-
C.
TX-14
TX-14 is a U.S. congressional district in Texas that elects a representative to the United States House of Representatives.
-
D.
TX-38
TX-38 is a U.S. congressional district in Texas represented in the House of Representatives.
-
E.
T-68
The T-68 was an early generation light rail tram used on the Manchester Metrolink system in the UK before being superseded by newer models.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada43954f0819096a96331bf3c53a8 |
completed | March 8, 2026, 4:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20394a8cc8190b114760079f8b0f6 |
completed | March 12, 2026, 12:06 a.m. |
| NEDg | Description generation | batch_69b20434da5081909871eb13cc0876ae |
completed | March 12, 2026, 12:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b20501301481908a7543db57a78546 |
completed | March 12, 2026, 12:12 a.m. |
Created at: March 8, 2026, 3:04 p.m.